Abstract
As a key grain-producing base and ecological barrier in China, the Chaohu Lake Basin plays a crucial role in ensuring food security and promoting high-quality ecological development. Uncovering the spatio-temporal evolution patterns and regional heterogeneity of agricultural non-point source pollution control efficiency within this basin is therefore crucial. Using panel data from 17 counties (districts) in the Chaohu Lake basin covering 2016–2023, this study adopts the SBM-DDF model to statically measure agricultural non-point source pollution control efficiency and applies the Global Malmquist-Luenberger (GML) index to dynamically decompose such efficiency. The findings indicate that: (1) Agricultural inputs in the Chaohu Lake basin are generally excessive, with the over-application of fertilizers and pesticides as the core issue, while the utilization efficiency of labor, machinery, and irrigation remains low. (2) Governance efficiency across entire river basins exhibits cyclical fluctuations characterised by ‘policy effectiveness—efficiency decline—adjustment recovery’. Furthermore, the findings reveal a weak synergy between technological advancement and management efficiency, which severely constrains overall governance effectiveness. (3) Significant regional heterogeneity exists: upstream areas exhibit higher excess inputs of labor, machinery, and pesticides, coupled with dual deficiencies in technology and management. Midstream regions demonstrate efficient land use and the lowest reliance on chemical pesticides, yet suffer from unstable policy implementation. Downstream areas are characterised by pronounced excesses in fertiliser and irrigation, alongside structural imbalances in technology and management. Based on these findings, this paper proposes targeted strategic recommendations to advance the green transformation of agriculture in the Chaohu Lake basin and achieve efficient control of non-point source pollution.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Funding
This study was funded by the National Key R&D Program of China (Grant No. 23YFD1702105-05).
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Qingyang He: Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing-Original draft preparation; Qinzhang Han: Methodology, Software, Data curation, Formal analysis. Weixue Lu: Methodology, Project administration, Supervision, Validation, Writing-Reviewing and Editing.
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He, Q., Han, Q. & Lu, W. Spatio-temporal evolution and regional heterogeneity in the efficiency of agricultural non-point source pollution control within the Chaohu Lake Basin. Sci Rep (2026). https://doi.org/10.1038/s41598-026-45974-4
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DOI: https://doi.org/10.1038/s41598-026-45974-4
